The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
It is frequently observed with raw images of this type that the image brightness in the marginal regions of the raw image is lower than in the center, although a homogeneous image brightness would be expected. A non-uniform brightness distribution is above all observed when the raw images were taken under oblique light incidence and/or an oblique taking angle.
Further factors can also be responsible for the named inhomogeneities in addition to an oblique light incidence and/or an oblique taking angle. Color filters e.g., which are disposed in front of a sensor matrix, can thus have angle-dependent characteristics. Furthermore, brightness drops in the marginal regions of a raw image—or very generally brightness inhomogeneities—are, however, also caused by imaging errors of an optical receiving system of the sensor. Finally, an inhomogeneous illumination of a surface to be observed can also be the cause for artifacts.
Artifacts of this type, which are caused by the sensor itself, by lighting devices or by distortion in the beam path of the received light, represent a not insubstantial interference factor. In particular with an optical detection of codes (e.g. for the identification of articles) by optoelectronic sensors or cameras, such parasitic inhomogeneities are irritating since they make error-free code recognition more difficult. It is known to avoid this problem to remove the named artifacts largely again by a suitable brightness correction (flat field correction).
Generally, flat field corrections are known for the compensation of deviating image brightness in the marginal region of an image. US 2005/0041850 A1, for example, describes a quality inspection system for wafers using a camera, with a flat field correction being carried out—in addition to other corrections—on the image taken by the camera. The effect of an angular incidence of an illumination light should be taken into account with the correction described. In this connection, a two-dimensional matrix of correction values k(x, y) are applied to the brightness values (intensity values) of the picture elements of the taken raw image. For this reason, just as many correction values as picture elements are required for this process. With a sensor which comprises 1280 picture elements in one direction (e.g. x direction) and 1024 picture elements in a direction perpendicular thereto (e.g. y direction), somewhat more than 1.3 million correction values therefore result, for example. Carrying out such a correction thus requires substantial memory space. The carrying out of the plurality of required computation operations and the accesses to the memory associated therewith are moreover very time-intensive.
However, it is particularly the time factor which is of particular importance for many applications. It is moreover desirable for a brightness-correcting process to be able to be carried out with electronic components which are as simple and therefore as cost-effective as possible.